The Effect of Caffeine Consumption on Sleep Quality among Undergraduate Students in Malaysia

This study aims to determine the effect of caffeine consumption on sleep quality among university students. This was a cross-sectional study that used a quantitative approach method. The data for this study was collected using a structured online questionnaire and distributed via online platforms to identify eligible participants. All the participants self-administered all three sections of the questionnaire, which were sociodemographic variables, the caffeine questionnaire tool, and the Pittsburgh Sleep Quality Index (PSQI). A chi-squared test was used to investigate the association between caffeine intake and sleep quality and the measured study characteristics. About 300 students, with a mean age of 21.95±1.43 years old, were recruited. The average caffeine intake of the study population was 193.54 mg per day. The respondents had good sleep quality was 44.7% while 55.3% had poor sleep. The study also found that there was a significant association between caffeine intake and sleep quality (p-value<0.01). Meanwhile, there was no significant association between sociodemographic characteristics and caffeine intake or sleep quality. This study shows that a student's excessive intake of caffeine is correlated with poor sleep quality. Therefore, prevention strategies should be used to raise awareness of the issue and understand how consuming too much caffeine might result in poor sleep quality.


INTRODUCTION
Caffeine is a naturally produced stimulant commonly present in tea, coffee, and cacao plants.It is stated that caffeine works by stimulating the brain and the central nervous system (Watson et al. 2016).The same study suggested that caffeine helps individuals in maintaining alertness and reducing the onset of fatigue.Nowadays, the use of caffeine is widespread, particularly among students.A research that was published in the National Library of Medicine found that 79% of college students who consume coffee also use caffeine to remain awake (Mahoney et al. 2019).According to the US Food and Drug Administration (FDA), healthy adults should not exceed 400 mg of caffeine per day in terms of recommended daily intake.
According to the Centers for Disease Control and Prevention (CDC 2022), people need to get plenty of sleep because it can have a negative impact on their health.Additionally, university students are included in the more than one-third of American people who habitually lack sleep.Adequate sleep is important for university students since it significantly influences their general health and well-being.To stay focused, enhance concentration, and enhance academic performance, students should get the recommended amount of sleep at night.Centers for Disease Control and Prevention (CDC) recommended that individuals between the ages of 18 and 60 should aim to obtain a minimum of seven hours of sleep per night to enhance their overall health and well-being.
Different studies have been done to determine the effect of caffeine consumption on the quality of sleep.A study conducted by AlSharif et al. (2018) found that most college Ikram et al.
students had poor sleep quality.This was caused by consuming too many caffeine-containing beverages.Another study by Ngu et al. (2017) stated that most pre-clinical medical students in Malaysia have poor sleep quality.In the same study, it was also proven that poor sleep quality was associated with caffeinated beverage intake.However, in another study, it was stated that there was no association between subjective sleep quality and the amount of caffeine consumed, with higher amounts of caffeine consumed related to decreased time in bed (Watson et al. 2016).
The general objective of this study is to determine the effects of caffeine consumption on sleep quality among undergraduate students in Malaysia.Meanwhile, the specific objectives are to determine the daily caffeine intake that students usually consume among undergraduate students in Malaysia.Secondly, to assess sleep quality over the past month among undergraduate students in Malaysia.Lastly, to investigate the association between caffeine consumption and sleep quality among undergraduate students in Malaysia.In Malaysia, there has not been much research about the association between caffeine intake and sleep quality.Nowadays, university students tend to consume caffeine in their daily lives to increase wakefulness, overcome fatigue, and enhance cognitive performance.This can have a significant impact on their ability to sleep and their overall performance.Hence, by conducting this study, it can show how caffeine intake is associated with sleep quality.

Design, location, and time
This was a cross-sectional study that uses a quantitative approach method.The location of the study was Malaysia.This includes both peninsular Malaysia and east Malaysia.This study was conducted among all undergraduate students in both public and private universities.The participants for this study will be undergraduate university students aged 18-24 years.The study was conducted from July 2022 to July 2023 among university students.The ethics application has been approved by the Faculty Ethics Review Committee (FREC), Universiti Teknologi MARA (UiTM), [reference number: FERC/FSK/ MR/2023/0037].

Sampling
The sample size for this study was 300 participants.The sample size was calculated using the RaoSoft sample size calculator with a 95% confidence level, a 5.61% error margin, and a 50% response distribution.A convenience sampling method was used for this study.This sampling method was chosen by using judgment and deliberate effort to pick Malaysian students who meet specific criteria for this study.The inclusion criteria for this study include undergraduate university students aged 18-24 years from all programme, and the participant must be able to understand English as the questionnaire will be in English only.The participation of the participants was completely unpaid and voluntary.Meanwhile, international students and those who did not meet all the criteria for this study were excluded.The consent form and an explanation about the study and procedure were distributed together with the questionnaire.

Data collection
The data for this study was collected through a structured online questionnaire and distributed via online platforms to identify eligible participants.The questionnaire consists of three sections: 1) sociodemographic variables (Lieberman et al. 2019) , which include age, gender, ethnicity, year of study, and type of university that the participants are currently staying at; 2) the caffeine questionnaire tool, where the participants will complete the 24hour recall caffeine questionnaire form (Bühler et al. 2013); and 3) the Pittsburgh Sleep Quality Index (PSQI), which was a self-reported questionnaire including 19 items that assessed sleep quality over the preceding month.The participants self-administered all three sections of the questionnaire.The consent form and an explanation about the study and procedure were distributed together in the questionnaire.

Data analysis
The Statistical Package for Social Scientists (SPSS) Version 27 statistical analysis was used to analyse the research findings and data.To provide descriptive results, the mean, standard deviation, frequency, and percentage were used.The continuous variable, age and average caffeine intake were computed as Standard Deviation (SD) and mean.For categorical variables, gender, Effect of caffeine consumption on sleep quality among students ethnicity, year of study, type of university, caffeine intake and sleep quality, frequency and percentages were utilized.Independent t-test was used to determine the association between age and sleep quality while, for the association of age and caffeine intake, One-way ANOVA was used.The association between caffeine intake and sociodemographic variables as well as the association between caffeine intake and sleep quality will be examined using the Chi-square test.A statistical test is considered significant when the p-value is below the threshold of 0.05 (p<0.05).

RESULTS AND DISCUSSION
Table 1.shows that the average age of the respondents is 21.95±1.43.In this study, 74.0% of the respondents are female students, while 26.0% are male, respectively.Based on the results, 18.7% of the participants were first-year students, followed by second-year (21.0%), third-year (48.3%), and fourth-year (12.0%).Among all respondents, 75.7% studied at a public university, while the other 24.3% studied at a private university.
Table 2 summarizes that 5.7% of the respondents reported no caffeine intake.In comparison, 80.0% of the respondents reported a tolerable caffeine intake, and the other 14.3% reported an excessive caffeine intake.Additionally, the average caffeine intake among the respondents was 193.54±142.74mg daily.
A study conducted in Bahrain reported that students' average daily caffeine intake was 268 mg (Jahrami et al. 2020).Kharaba et al. (2022) found that the average intake of caffeine for the total population of the study was 264 mg per day.In addition, Mahoney et al. (2019) found that the average caffeine intake was 159 mg daily in five universities in the United States, The present study found that most university students (94.3%) consumed caffeine.The results were from students who had caffeine in a tolerable and excessive amount.Lohsoonthorn et al. (2013) stated in their study that 58% of students used stimulant beverages.In another study that was conducted at a public university in Malaysia, the mean daily caffeine intake among the students was 67.98% (Isa et al. 2021).A study conducted at a private university in Malaysia reported that most students consume caffeine from tea, coffee, soft drinks, and chocolate drinks (Isa et al. 2021).Most young adults consume a lot of energy drinks and other stimulants to avoid falling asleep and increase their academic performance (Sanchez et al. 2013).It was also reported that students consume caffeinated beverages to increase alertness and concentration during study, polish their memory,  Peng et al. 2020).
Table 3 shows there was no association between sociodemographic variables (age, gender, ethnicity, year of study, type of university) and caffeine intake among undergraduate students in Malaysia.There was no association between gender and caffeine intake.This finding was supported by a study conducted at Zayed University in Dubai, which reported no association between gender and caffeine intake (M Al Ghali et al. 2017).Inconsistent with our findings, there was an association found between gender and caffeine intake, as female respondents have a higher average caffeine intake compared to male respondents (Kharaba et al. 2022).
A study conducted among the US adult population reported that ethnicity strongly shows an association between ethnicity and caffeine intake (Lieberman et al. 2019).However, there is a lack of literature and discussion about the association between ethnicity or race and caffeine intake.In contrast, a study conducted at Florida State University among college students reported that levels of education were associated with caffeine intake.Additionally, it is found that people at higher levels of education usually consume more caffeine than those at lower levels of education (Bertasi et al. 2021).Limited studies also look for an association between years of study and caffeine.Additionally, there is a lack of literature about this relationship and a weak line between this association Table 4 shows the results of the frequency and percentage of sleep quality among the respondents.Sleep quality was categorised into In the present study, 55.3% of the respondents showed poor sleep quality.The reasons half of the students had poor sleep quality might be related to their coursework, assignments, and activities at the university (Emmy et al. 2023;Ab Hamid et al. 2021).The present results were in line with previous studies.In a study in Ethiopia, Lemma et al. (2012) reported that more than half of the students (55.8%) had poor sleep quality.The prevalence of poor sleep quality was higher among university students in Saudi Arabia at 80% (AlSharif et al. 2018), which is higher than the present study.A study from Thailand reported that 48.1% of the participants had poor sleep quality (Lohsoonthorn et al. 2013).Most students consume caffeine to stay awake and result in poor sleep quality (Zhang et al. 2022).Many factors contribute to poor sleep quality, such as noise, cigarette smoke, and the quality of the air (Altun et al. 2012).Sleeping in a room with exposure to tobacco was the most chosen reason for poor sleep quality for half the college students (Altun et al. 2012).
Sociodemographic variables such as age, gender, ethnicity, year of study, and type of university were found to have no statistical association with sleep quality.According to Mahoney et al. (2019), there is no correlation between gender and sleep quality, which is in line with the findings of this study.Even the study's results indicate that male students are likelier than female students to have poor sleep quality.However, there was no association between these two characteristics.However, it was reported female students have poor sleep quality compared to male students in Saudi Arabia (AlSharif et al. 2018).Nevertheless, the present study result is at par with a study done in Malaysia, which found no statistical association between ethnicity and sleep quality (Yi et al. 2022).
There was no association between the year of study and sleep quality.The reasons might be due to different coursework and academic schedules that eventually lead to the student's daily routine.In line with the current study, a study conducted in Korea reported that grade was not associated with sleep quality among nonsmoking students (Choi 2020).However, there was a lack of clarification and discussion about the relationship between the current semester and sleep quality.
Table 5 highlighted that there was a significant association between caffeine intake and sleep quality among undergraduate students in Malaysia (p<0.01).The results of this study are in line with previous studies.A study conducted in Saudi Arabia stated that 476 college students with high caffeine intake had poor sleep quality   (2018) stated that caffeine can improve performance; however, the most known side effect is sleep deprivation.One study found that 400 mg of caffeine taken 0, 3, or 6 hours before bedtime significantly interrupts sleep, and the findings for this study also stated that even at 6 hours, caffeine reduces sleep time by more than an hour (Drake et al. 2013).Snel and Lorist (2011) reported in their study that caffeine is one of the stimulants that can produce harmful effects on sleep quality, as it has already proven its effectiveness in counteracting sleepiness.Adenosine increases drowsiness, improves slow wave activity during sleep, and lowers the electroencephalogram (Nehlig 2015), while caffeine, an adenosine-receptor antagonist, primarily affects performance via occupying the adenosine receptor (Van Donghen et al. 2001).Additionally, caffeine acts primarily on adenosine A1 and adenosine A2A receptors that are related to the function of the brain and are associated with sleep, arousal, and cognition (Ribeiro & Sebastio 2010).In another study, it is mentioned that the presence of caffeine and its main paraxanthine will trigger a change in the adenosine system and will affect sleep (Reichert et al. 2022).

CONCLUSION
In conclusion, this study also demonstrates that the majority of the study population consumes caffeine daily while more than half of university students had poor sleep quality.This study also highlighted that there is an association between caffeine intake and sleep quality among undergraduate students in Malaysia.
Hence, to limit daily caffeine intake among students, individuals and the community need to spread awareness regarding this issue so that they become more aware of the negative health outcomes that will happen to them.In addition, the university also plays an important role in handling this issue, as they can limit the number of vending machines that sell caffeinated beverages to reduce the caffeine intake among university students.

Table 3 .
The association between sociodemographic factors and caffeine intake of the participants (n=300) SD: Standard Deviation; a One-Way ANOVA reported is in F (df) p-value; b Chi-square test reported is in X2 (df) and p-value

Table 4 .
Sleep quality of the participants (n= 300)

Table 5 .
The association between caffeine intake and sleep quality of the participants using Chi square test (n=300) b Chi-square test reported in X2 (df) and p-value; * Significant of p-value< 0.01